The market's visibility to early quality issues has never been greater and will continue to accelerate. The extensive awareness creates opportunities for the prepared enterprise, and substantial risks for those slow to react.

The system includes NVIDIA’s Deep Learning software stack and NGC containers. Immediately after installation, the system was ready to train models and scale Vyasa’s software. The easy-to-use DIGITS deep learning training system and interface available on DGX-1 helps users manage training data, monitor performance, and design, compare and select networks.

Microway’s NumberSmasher Tesla GPU Servers integrate 1–10 NVIDIA Tesla V100 GPUs with flexible GPU density. These servers are fully configurable for any customized workload. The Vyasa Analytics deployment utilized this configurability to deploy early R&D environments and test new concepts—scaled up onto the DGX-1 when ready.

Vyasa Analytics provides a deep learning analytics platform for organizations in the lbusiness intelligence verticals. Vyasa’s scalable deep learning software, Cortex, operating on NVIDIA GPUs and Microway server hardware, applies deep learning-based analytics to enterprise data of a variety of types: text, image and more. Use cases include analyzing multiple large-scale text sources and streams that include millions of documents in order to discover patterns, relationships, and trends.

“These systems have enabled us to branch out into a number of R&D areas that were really critical for us to be able to innovate and build out new types of deep learning approaches,” says Dr. Christopher Bouton, founder and CEO of Vyasa Analytics. “As a company working in the deep learning space, we see Microway and NVIDIA as key partners in our ability to build innovative novel deep learning algorithms for a wide range of content types.”